Do Accelerators Work? If So, How?

By Benjamin L. Hallen, Susan L. Cohen, Christopher B. Bingham. Organization science (Providence, R.I.), 2020

236 citations recorded by the source corpus.

A fundamental challenge for new ventures is overcoming liabilities of newness - particularly, lack of relevant knowledge. Accelerators, intense, time-compressed entrepreneurial programs, attempt to alleviate these liabilities by providing ventures with intensive learning. While accelerators have rapidly emerged as prominent players in the entrepreneurial ecosystem, entrepreneurs, policy makers, and other practitioners have continued to raise questions about their efficacy. Mirroring such concerns, extant organizational theories offer competing predictions about whether and for which ventures accelerator participation might be beneficial. Drawing on hybrid empirical methods that triangulate across multiple quantitative and qualitative analyses, we consistently find evidence that many accelerators do indeed aid and accelerate venture development and that their effects are neither due purely to selection or credentialing. Intriguingly, our results also indicate that accelerator participation complements rather than substitutes for many forms of prior founder experience (e.g., having worked for a company that produces a lot of startups). Overall, we contribute by pioneering work on the nature and outcomes of accelerators, offering insight into the fundamental value of intensive indirect learning (vs direct learning) in new ventures and extending understanding of how organizations may speed products and services to market.

Subfields: Accounting, Economics and Econometrics, Management of Technology and Innovation

View Paper: https://www.semanticscholar.org/paper/ed925ed0ef0592c141722273bbbeac5a41cbdfa0

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Citations in the corpus

Strategy and Uncertainty: Resource-Based View, Strategy-Creation View, and the Hybrid Between Them (2021, background): “In a related study, Hallen, Cohen, and Bingham (2020) find that deep and early discussions to develop a mental model, followed by trial-and-error and experimentation learning, was most effective for creating strategy.”